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GitLab
vs
Azure Monitor
Decision Kit
Decision Kit
Azure monitor vs gitlab

Summary

Azure Monitor is a Microsoft tool for collecting and analyzing metrics from your cloud and on-premises environments. It provides insight on how applications are performing, and identifies issues affecting them and the resources they depend on. Data collected by Azure Monitor fits into one of two types: metrics and logs. Metrics are numerical values that describe some aspect of a system at a particular point in time. Logs contain different kinds of data organized into records, with different sets of properties for each type.

GitLab has a powerful monitoring capability with Prometheus, a time-series monitoring service, providing a flexible platform for monitoring GitLab and other software products. GitLab provides out of the box monitoring with Prometheus, providing easy access to high quality time-series monitoring of GitLab services. GitLab has built-in monitoring that can automatically monitor your deployed applications, with extensive support for native cloud, container, and microservices technology. Additionally, Gitlab uses Jaeger, an open source end-to-end distributed tracing system used for monitoring and troubleshooting microservices-based distributed systems.

Resources

Feature Comparison
FEATURES

Cloud Native Monitoring

The monitoring of cloud native applications including microservices that are built to run in the cloud so that bottlenecks and issues can be addressed via insights into collected metrics.

Server Monitoring

Reviewing and analyzing a server for availability, operations, performance, security and other operations-related processes. Monitor servers system resources like CPU Usage, Memory Consumption, I/O, Network, Disk Usage, Process, etc. GitLab uses the Node Exporter (via Prometheus) to expose an extensive set of machine-level metrics on Linux and other Unix systems such as CPU usage, memory, disk utilization, filesystem fullness, and network bandwidth.

Tracing

Tracing provides insight into the performance and health of a deployed application, tracking each function or microservice which handles a given request. This makes it easy to understand the end-to-end flow of a request, regardless of whether you are using a monolithic or distributed system.

Learn more about Tracing